One of the most pressing challenges in responding to the emergence of novel henipaviruses is the widespread lack of integrated genomic and serological surveillance systems. In many low- and middle-income countries (LMICs), particularly across Asia where henipavirus outbreaks have occurred and in parts of Africa where henipaviruses or their natural hosts have been identified (Supplementary Figures S1, S3), surveillance remains limited or narrowly focused on known pathogens, leaving divergent henipavirus strains undetected. For instance, WHO reported that one in three countries (about 33%) do not have in-country genomic surveillance capacity for pathogens (World Health Organization, 2022), despite the major investments made in genomic surveillance in response to the COVID-19 pandemic. Even fewer countries have established comprehensive serological monitoring that spans human, animal, and wildlife species (Schulz et al., 2020; Akoi Bore et al., 2024). Moreover, most surveillance efforts are disease-specific and fail to capture the broader virome present in wildlife or the environment. This fragmented approach hampers early warning capabilities, delaying outbreak detection and impeding rapid response, as seen in some previous spillover events of NiV where rapid and early case identification was not available (Hassan et al., 2025). Similarly, the identification of MojV as the etiological agent for fatal cases of pneumonia was established six months after the initial outbreak that occurred in an abandoned mine in Yunnan province (Wu et al., 2014).

To close critical knowledge and preparedness gaps related to novel and under-characterized henipavirus species, there is an urgent need to strengthen surveillance systems across both animal and human health domains (Supplementary Figure S4). A top priority is the expansion of genomic and serological surveillance in wildlife reservoirs, particularly bats, shrews, and rodents that have been identified as natural hosts or potential carriers, with coordinated sampling in human populations living in at-risk areas (Moore et al., 2024). To improve efficiency and impact, surveillance should be geographically targeted using spatial risk mapping that integrates ecological and environmental determinants of spillover risk, such as land-use change, climate variability, and host species distribution (Sun et al., 2024). By aligning surveillance activities with areas where cross-species transmission is most likely, data can be generated to identify high-risk interfaces (e.g., bat-livestock-human contact zones, wildlife markets) and to guide preventive interventions. Standardized protocols for specimen collection (e.g., blood, oral swabs, urine, feces) and sequencing workflows are needed to ensure both the quality and comparability of datasets across studies and regions. Strengthening surveillance also requires clear data governance frameworks to ensure timely but responsible sharing of genomic and epidemiological data across sectors and borders. Equally important are enabling conditions for safe wildlife sampling practices that emphasize personal protective equipment, cold chain maintenance, and biosafety standards.

Within this broader framework, serological surveillance plays a particularly important role in detecting past exposure and silent transmission, especially in the absence of active infection (Supplementary Figure S4) (Wang et al., 2023). Currently, assays are available only for NiV, HeV, LayV, and Cedar virus (largely limited to in-house or research-use platforms, as no commercialized diagnostic kits are available), but interpretation remains complicated by cross-reactivity with other paramyxoviruses. Using more specific antigens (e.g., glycoprotein or prefusion proteins) together with a tiered approach, such as ELISA or bead-based multiplex assays screening followed by neutralization assays, is recommended (Fischer et al., 2018). Such approaches not only enhance diagnostic accuracy but also provide more reliable data for understanding the true extent of henipavirus circulation in humans and animal reservoirs.

In tandem with environmental and animal surveillance, there is a critical need to establish longitudinal human cohort studies focusing on patients presenting with febrile, respiratory and neurological syndromes – clinical manifestations that may signal early or atypical henipavirus infections. Continuous clinical surveillance and systematic biobanking of patient samples in endemic or high-risk areas can facilitate the detection of emerging or cryptic viral threats. Integrating these patient-based cohorts with genomic diagnostics, metagenomic sequencing, and syndromic surveillance frameworks will enhance early outbreak detection and allow for better characterization of clinical spectrum and disease burden. Such cohort-based studies are especially important in resource-limited settings, where underdiagnosis is common and disease etiology often remains unresolved. Case surveillance studies have shown an alarmingly high frequency of febrile illnesses (~60%) (Rainey et al., 2022) and acute meningitis and encephalitis (~70%) (Wang et al., 2022) of unknown etiology, signaling under-detection of known and possibly novel pathogens, and point to systemic blind spots in diagnostic capacity and disease surveillance. Expanding access to syndromic and genomic surveillance will be essential to closing these gaps. Strengthening this clinical surveillance pillar alongside environmental and animal health monitoring is essential to building a comprehensive, real-time early warning system for henipaviruses (Supplementary Figure S4).

In the regional context of disease surveillance in China, sustained investment in laboratory capacity, including next-generation sequencing and biospecimen repositories, is critical for rapid detection and long-term monitoring. Yunnan province, where MojV and Yunnan bat henipaviruses 1 and 2 have been detected, is particularly vulnerable to cross-species transmission due to its exceptional biodiversity. The Yunnan Provincial Center for Disease Control and Prevention (CDC), for example, has been central to surveillance and genetic characterization of novel henipaviruses, bat coronaviruses, and other high-risk zoonoses in southern China (Luo et al., 2018; Yang et al., 2023; Kuang et al., 2025). Its continuous field sampling and collaborative virus discovery efforts have contributed valuable genomic data to global early warning systems.

At the policy level, cross-border surveillance networks, capacity building, and real-time data sharing are critical to accelerate recognition of emerging threats and enable timely public health responses. Because southern China and mainland Southeast Asia are linked by ecologically connected, transboundary habitats, the risk of henipavirus spillover extends across rather than within national boundaries. Yunnan province, which borders Myanmar, Laos, and Vietnam, is a region of particular concern. Strengthening cross-border collaboration is therefore essential. The Mekong Basin Disease Surveillance (MBDS) network has facilitated joint outbreak investigations, data governance and sharing, and workforce training since the early 2000s (Mekong Basin Disease Surveillance (MBDS) network, 2025), and renewed post-COVID-19 momentum offers an opportunity to reinvigorate this platform with a focus on emerging zoonoses. Likewise, the Association of Southeast Asian Nations (ASEAN)-China Health Cooperation has advanced diagnostics, surveillance, and preparedness through regional dialogue and technical collaboration (ASEAN-China Health Cooperation, 2024). Proactive inclusion of henipaviruses within these health security agendas is both timely and necessary, and we propose establishing a joint framework that bridges ASEAN-China platforms with Bangladesh and India to strengthen preparedness across the wider Asian corridor of risk.

Despite growing global recognition of the One Health approach, its implementation remains fragmented and inconsistent across countries and sectors. Human, animal, and environmental health sectors often continue to function independently, hindering data sharing and joint risk assessment. The natural hosts of henipaviruses and related henipa-like orthoparamyxoviruses are now documented in more than 130 countries and territories (Figure 1; Supplementary Table S1), underscoring a wider potential for spillover than previously recognized. However, geographic presence does not equate to local abundance, and neither distribution nor density alone determines spillover risk, which is shaped by additional ecological and anthropogenic factors. Critical interfaces such as those between wildlife, livestock, and humans remain under-studied, particularly in rural and peri-urban settings where risk is likely elevated. A recent global assessment reported that formal coordination mechanisms across One Health sectors are underdeveloped in many LMICs (Zhang et al., 2024). Additionally, ecosystem-level drivers of disease emergence, including deforestation, agricultural intensification, and biodiversity loss, are rarely monitored in tandem with health surveillance systems. Southeast Asia, a known hotspot for zoonotic spillovers, has experienced rapid land-use changes, with over 60 million hectares of forest lost in the last two decades (Feng et al., 2021), intensifying contact between wildlife and human populations (Sanchez et al., 2022). Without stronger intersectoral coordination and environmental monitoring, the world remains vulnerable to future henipavirus outbreaks and other zoonotic threats.

Effective implementation of the One Health approach for henipavirus prevention requires a research agenda that addresses critical gaps in transmission ecology and environmental risk. One priority area is the characterization of viral shedding dynamics in reservoir and intermediate hosts, particularly bats, shrews, and livestock species. Longitudinal surveillance studies that monitor viral shedding in host urine across different seasons and physiological states (e.g., breeding, gestation, or migration) could help identify temporal patterns associated with increased zoonotic risk (Plowright et al., 2015). Such data, when coupled with ecological and climatic variables, would enable more accurate modeling of spillover risk and inform targeted interventions at high-risk interfaces.

Spatial risk models that integrate remote sensing data, species distribution records, and land-use change metrics offer a promising tool for predicting potential hotspots of viral emergence (Plowright et al., 2021; Carlson et al., 2022). By combining satellite-derived environmental indicators (e.g., vegetation cover, rainfall anomalies, temperature shifts) with high-resolution maps of host and reservoir species distributions, these models can capture ecological conditions that facilitate viral maintenance and transmission. Incorporating land-use dynamics, such as deforestation, agricultural expansion, and urban encroachment, further helps identify areas where human activities increase contact with wildlife reservoirs (Jones et al., 2013). Operationalizing these insights requires a dashboard of environmental drivers that integrates deforestation alerts, livestock density data, and culturally relevant risk practices (e.g., unprotected date palm sap harvesting) into a public, quarterly updated platform. Such a tool enables real-time monitoring of spillover drivers and issues timely advisories to national and regional stakeholders. Measurable outputs include the public availability of the dashboard, the number of risk advisories generated, and documented evidence of their uptake in preparedness actions. Together, these integrated approaches can pinpoint geographic zones of elevated spillover risk and support scenario-based forecasting, providing evidence to guide targeted surveillance, early warning systems, and preventive interventions (Supplementary Figure S4).

Diagnostic capacity for henipaviruses remains severely constrained, with testing confined to a limited number of specialized reference laboratories equipped with advanced biosafety facilities (World Health Organization, 2022). This gap represents a critical barrier to timely outbreak detection and case confirmation, especially in regions at highest risk of zoonotic spillover. A recent survey highlighted that fewer than 20% of health facilities in low-income settings, particularly across Africa, had access to diagnostic platforms, even for high-burden diseases such as HIV/AIDS and malaria (Yadav et al., 2021), underscoring the magnitude of inequities in laboratory capacity. Within this context, point-of-care assays and rapid diagnostic tools for henipaviruses remain scarce, especially in rural and high-risk regions where they are most needed (Hassan et al., 2025).

Addressing these diagnostic gaps requires urgent investment in both tool development and system-level strengthening (Okeke and Ihekweazu, 2021). A priority is the development and validation of multiplex PCR assays and rapid antigen tests capable of detecting a broad range of known and novel henipaviruses, enabling differential diagnosis in febrile, respiratory, and encephalitic illness presentations. While metagenomic sequencing offers unparalleled breadth for pathogen discovery, its implementation in low-resource settings is constrained by cost, infrastructure requirements, and technical complexity, making multiplex PCR a more feasible frontline solution. Equally critical is the establishment of global validation pipelines, such as WHO prequalification and regional reference standards, to ensure diagnostic accuracy and comparability across platforms.

Emerging point-of-care platforms such as reverse transcription loop-mediated isothermal amplification (RT-LAMP), reverse transcription recombinase polymerase amplification (RT-RPA), and CRISPR-based assays offer promising alternatives for rapid detection of NiV and HeV (Pollak et al., 2022; Miao et al., 2023; van den Hurk et al., 2025). Compared with multiplex PCR, these methods are generally faster, easier to use, and less reliant on advanced laboratory infrastructure, which makes them attractive for deployment in resource-limited settings (Supplementary Table S2). They also have the potential to reduce costs and cold-chain dependence, although reagent stability in tropical environments remains a challenge. CRISPR-based assays, in particular, offer high specificity through programmable guide RNAs, but like other isothermal methods, they remain in early development or validation with limited performance data, constraining their immediate application for large-scale surveillance or outbreak response. It is also important to note that primer and probe design for henipavirus assays requires particular attention to lineage divergence within the G, N, and F genes. For broad coverage, degenerate primers or pooled primer sets are often necessary, complemented by in silico inclusivity analyses against all available NiV and HeV sequences. Such analyses are essential to ensure that assays can reliably detect both prototype and divergent strains, and to minimize false negatives when applied in surveillance across regions where multiple lineages co-circulate. Therefore, while these assays represent promising complements to multiplex PCR, significant hurdles must be overcome before they can reliably support henipavirus surveillance and outbreak response. Accordingly, multiplex RT-PCR remains the primary clinical confirmatory method (Guillaume et al., 2004; Feldman et al., 2009; Mazzola and Kelly-Cirino, 2019), while isothermal and CRISPR-based assays are better positioned for field screening and surge triage pending further validation.

Expanding local laboratory capacity, especially in LMICs where spillover risk is concentrated, will require improving assay performance, strengthening regional networks, workforce training, and collaborative technology transfer. Together, these measures are essential to close the diagnostic divide and enhance early detection of henipavirus spillover events.

While genomic characterization and molecular diagnostics remain central to henipavirus detection and surveillance, it is important to note that functional virological assays are often required to assess host range and zoonotic potential of newly identified henipaviruses. In particular, pathogenic henipaviruses such as NiV and HeV are known to utilize the highly conserved ephrin-B2 and ephrin-B3 cellular receptors, a feature that underpins their broad mammalian tropism and severe pathogenicity (Bonaparte et al., 2005; Negrete et al., 2005). Accordingly, receptor-binding and pseudotyped virus entry assays, as well as reverse-genetics-based systems, have been widely employed to interrogate viral entry, fusion efficiency, and replication competence across species (Yun et al., 2015). Comprehensive descriptions of functional approaches for receptor usage studies and reverse-genetics platforms for henipaviruses have been reported elsewhere, and are not further discussed in this article, which focuses on molecular diagnostics and detection strategies applicable to surveillance and outbreak settings.